Recent Advances in Feature Detectors and Descriptors: A Survey
- Authors
- Lee, Haeseong; Jeon, Semi; Yoon, Inhye; Paik, Joonki
- Issue Date
- Jun-2016
- Publisher
- 대한전자공학회
- Keywords
- Keypoints; Feature detection; Feature description; Image matching; Invariant features; Computational cost
- Citation
- IEIE Transactions on Smart Processing & Computing, v.5, no.3, pp 153 - 163
- Pages
- 11
- Journal Title
- IEIE Transactions on Smart Processing & Computing
- Volume
- 5
- Number
- 3
- Start Page
- 153
- End Page
- 163
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/8089
- ISSN
- 2287-5255
- Abstract
- Local feature extraction methods for images and videos are widely applied in the fields of image understanding and computer vision. However, robust features are detected differently when using the latest feature detectors and descriptors because of diverse image environments. This paper analyzes various feature extraction methods by summarizing algorithms, specifying properties, and comparing performance. We analyze eight feature extraction methods. The performance of feature extraction in various image environments is compared and evaluated. As a result, the feature detectors and descriptors can be used adaptively for image sequences captured under various image environments. Also, the evaluation of feature detectors and descriptors can be applied to driving assistance systems, closed circuit televisions (CCTVs), robot vision, etc.
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Collections - Graduate School of Advanced Imaging Sciences, Multimedia and Film > Department of Imaging Science and Arts > 1. Journal Articles
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